You can install cppdoubles
using the below code.
::install_github("NicChr/cppdoubles") remotes
Comparing equality of 2 double vectors
library(cppdoubles)
### Basic usage ###
# Standard equality operator
sqrt(2)^2 == 2
#> [1] FALSE
# approximate equality operator
sqrt(2)^2 %~==% 2
#> [1] TRUE
Other approximate equality operators
sqrt(2)^2 %~>=% 2
#> [1] TRUE
sqrt(2)^2 %~<=% 2
#> [1] TRUE
sqrt(2)^2 %~>% 2
#> [1] FALSE
sqrt(2)^2 %~<% 2
#> [1] FALSE
# Alternatively
double_equal(2, sqrt(2)^2)
#> [1] TRUE
double_gte(2, sqrt(2)^2)
#> [1] TRUE
double_lte(2, sqrt(2)^2)
#> [1] TRUE
double_gt(2, sqrt(2)^2)
#> [1] FALSE
double_lt(2, sqrt(2)^2)
#> [1] FALSE
All comparisons are vectorised and recycled
double_equal(sqrt(1:10),
sqrt(1:5),
tol = c(-Inf, 1e-10, Inf))
#> [1] FALSE TRUE TRUE FALSE TRUE TRUE FALSE FALSE TRUE FALSE
One can check if a double is a whole number like so
# One can check for whole numbers like so
<- function(x, tol = getOption("cppdoubles.tolerance", sqrt(.Machine$double.eps))){
whole_number double_equal(x, round(x), tol = tol)
}<- seq(-5, 5, by = 0.2)
x <- x[whole_number(x)]
whole_nums
whole_nums#> [1] -5 -4 -3 -2 -1 0 1 2 3 4 5
all_equal
as an alternative to base R
all.equal.numeric
<- seq(0, 10, 2)
x <- sqrt(x)^2
y
all_equal(x, y)
#> [1] TRUE
all_equal(x, 1)
#> [1] FALSE
all_equal(x, NA)
#> [1] NA
isTRUE(all_equal(x, NA))
#> [1] FALSE
Benchmark against all.equal.numeric
library(bench)
<- abs(rnorm(10^7))
x <- sqrt(x)^2
y <- x^2
z
# 2 approximately equal vectors
mean(rel_diff(x, y))
#> [1] 7.760502e-17
mark(base = isTRUE(all.equal(x, y)),
cppdoubles = all_equal(x, y))
#> # A tibble: 2 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 base 367ms 380ms 2.63 437MB 9.22
#> 2 cppdoubles 156ms 157ms 6.38 0B 0
# 2 significantly different vectors
mean(rel_diff(x, z))
#> [1] 0.4627624
mark(base = isTRUE(all.equal(x, z)),
cppdoubles = all_equal(x, z))
#> # A tibble: 2 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:tm> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 base 261.7ms 273.2ms 3.66 343MB 7.32
#> 2 cppdoubles 2.3µs 2.5µs 361935. 0B 0
Benchmark against using absolute differences
mark(double_equal(x, y),
abs_diff(x, y) < sqrt(.Machine$double.eps))
#> # A tibble: 2 × 6
#> expression min median `itr/sec` mem_alloc `gc/sec`
#> <bch:expr> <bch:t> <bch:t> <dbl> <bch:byt> <dbl>
#> 1 double_equal(x, y) 170.7ms 174.1ms 5.76 38.1MB 0
#> 2 abs_diff(x, y) < sqrt(.Machine$d… 68.2ms 68.9ms 14.5 114.4MB 29.0